Research activity

Complexity of disease dynamics

The study of disease dynamics is one of the fundamental applications of complexity science. Our research in this line is devoted to the understanding of the fundamental role of geography in the spread dynamics of infectious diseases.

We use an in-house advanced state-of-the-art simulation engine for individual based simulations of disease dynamics. The engine offers several features to set up and execute massive large scale simulations: its advanced capabilities can be grouped into five major features:

1. It allows the simulation of large scale geographic spread of infections on high resolution maps. Any combination of resolution and size is possible: we are only limited by computational resources.
2. It features a code generator which permits implementation of complex epidemiological models in a breeze. Models can be written in text files using a format very similar to their description with pencil and paper: the code generator will take the model description and produce an executable ready for submission.
3. It permits to assign specific user-defined data to individuals: for instance individual immunity profiles or whatever kind of static/dynamic information individuals possess.
4. It provides mechanisms for advanced simulation control via user-defined functions. These can be used, for example, to alter the execution according to specific conditions occurring during the simulation.
5. The simulation engine produces fully parallelized code which can be submitted on a computer cluster. User-defined function have access to simple mechanisms for data reduction and sharing of user-defined data not handled directly by the simulation engine.

The development of the simulation engine is driven by research. Hence it is under constant revision and upgrade with novel functionalities.

Applications

Our simulation engine has been used to explore the dynamics and geographic spread of measles in the pre-vaccination era, and is currently being used to explore measles dynamics in the post-vaccination era, multi-strain flu dynamics and dengue dynamics.

Interested in joining?

1. Periodicity, synchronization and persistence in pre-vaccination measles
   Ramona Marguta and Andrea Parisi
   J. R. Soc. Interface, 13, 20160258 (2016)   doi: 10.1098/rsif.2016.0258   [Abstract]

2. Human mobility and the Dynamics of Measles in Large Geographical Areas
   Ramona Marguta and Andrea Parisi
   in "Proceedings of ECCS 2014", Springer Proceeding in Complexity. S. Battiston et al. (eds.), pp 169-179 (2016)   doi: 10.1007/978-3-319-29228-1_15  

3. Power law jumps and power law waiting times, fractional calculus and human mobility in epidemiological systems
   Nico Stollenwerk, Urszula Skwara, Lidia Aceto, Eric Daude, Ramona Marguta, Luís Mateus, Peyman Ghaffari, Andrea Parisi and Maíra Aguiar
   in "Proceedings of the 14th Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2015",
   ed. by J.V.-Aguiar, CMMSE (2015)     pp. 1073-1268   [PDFormat]

4. Impact of human mobility on the periodicities and mechanisms underlying measles dynamics
   Ramona Marguta and Andrea Parisi
   J. R. Soc. Interface, 12, 20141317 (2015)   doi: 10.1098/rsif.2014.1317   [Article explained]

5. Human mobility and measles
   Ramona Marguta and Andrea Parisi
   in "Proceedings of the 14th Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2014",
   ed. by J.V.-Aguiar, CMMSE (2014)     Vol. 3, pp. 868-870   [PDFormat]

6. Stochastic amplification and childhood diseases in large geographical areas
   Ramona Marguta and Andrea Parisi
   in "Proceedings of the 13th Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2013",
   ed. by I.P. Hamilton & J.V.-Aguiar, CMMSE (2013)     Vol. 3, pp. 1001-1005   [PDFormat]

7. Stochastic fluctuations in the susceptible-infective-recovered model with distributed infectious periods
   A.J. Black, A.J. McKane, A. Nunes and A. Parisi
   Physical Review E, 80(2), 021922 (2009)
   also listed in Virtual Journal of Biological Physics Research 18(5), September-1 2009

8. Heterogeneity in antibody range and the antigenic drift of influenza A viruses
   A. Parisi, J.S. Lopes, A. Nunes, G. Gomes
   Ecological Complexity, 14, 157 (2013). doi:10.1016/j.ecocom.2012.12.001

9. Detecting and describing dynamic equilibria in adaptive networks
   S. Wieland, A. Parisi, A. Nunes
   European Physics Journal - Special Topics, 212(1), 99-113 (2012)     [Preprint]

10. Characterizing Steady-State Topologies of SIS Dynamics on Adaptive Networks
    S. Wieland, T. Aquino, A. Parisi, A. Nunes
    in "Proceedings of the European Conference on Complex Systems ECCS2010"     [Preprint]